Hi HN! I've been working on two novel programming languages built on field theory
from superconductor research.
*WPE/TME* - A geometric calculus language for structural and temporal reasoning.
Think: mathematical notation for encoding semantic relationships. Four parameters
(domain, shell, phase, curvature) let you explicitly represent how components
couple, influence each other hierarchically, and evolve over time.
*Crystalline* - A code synthesis language that generates provably optimal code
through physics-guided evolution. Not template filling. It discovers novel
optimizations (async I/O, streaming, parallelization, loop fusion) through energy
minimization, achieving 3-4× performance improvement.
Both languages share the same geometric foundation from superconductor physics but
serve completely different purposes. WPE/TME is for semantic reasoning (great for
LLM scaffolding). Crystalline is for generating high-performance code.
Key differences from existing approaches:
- Deterministic (same input always produces same output)
- Explainable (energy equations show WHY decisions were made)
- Novel code generation (genuinely discovers optimizations)
- Mathematical guarantees on performance
Crystalline has a Python implementation. WPE/TME has a Python reference
implementation, but it's really a notation system (like how LaTeX is a language
for typesetting math).
GitHub: [will add link on launch day]
Papers: [will add ResearchGate links - 3 papers explaining theory]
I'd love feedback on:
1. The language design - does geometric encoding make sense?
2. For Crystalline: what benchmarks would convince you the synthesis works?
3. For WPE/TME: would explicit structure help your AI reasoning tasks?
Happy to answer questions about the physics, the languages, or the implementations!
